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» Predicting mining activity with parallel genetic algorithms
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ECML
2007
Springer
14 years 1 months ago
Multi-objective Genetic Programming for Multiple Instance Learning
Abstract. This paper introduces the use of multi-objective evolutionary algorithms in multiple instance learning. In order to achieve this purpose, a multi-objective grammar-guided...
Amelia Zafra, Sebastián Ventura
DEXAW
1998
IEEE
116views Database» more  DEXAW 1998»
13 years 12 months ago
Data-Mining: A Tightly-Coupled Implementation on a Parallel Database Server
Due to the increasingly di culty of discovering patterns in real-world databases using only conventional OLAP tools, an automated process such as data mining is currently essentia...
Mauro Sousa, Marta Mattoso, Nelson F. F. Ebecken
EC
2008
157views ECommerce» more  EC 2008»
13 years 6 months ago
The Crowding Approach to Niching in Genetic Algorithms
A wide range of niching techniques have been investigated in evolutionary and genetic algorithms. In this article, we focus on niching using crowding techniques in the context of ...
Ole J. Mengshoel, David E. Goldberg
GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
13 years 11 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
FPGA
2006
ACM
224views FPGA» more  FPGA 2006»
13 years 11 months ago
Flexible implementation of genetic algorithms on FPGAs
In this paper, we propose a technique to flexibly implement genetic algorithms for various problems on FPGAs. For the purpose, we propose a basic architecture for GA which consist...
Tatsuhiro Tachibana, Yoshihiro Murata, Naoki Shiba...